1. Field
The following description relates to technology to detect and analyze faults of an electronic device, and more particularly, to a device that can automate fault detection and analysis of a smart device.
2. Description of the Related Art
Recently, personal terminals designed to perform only a specific function, for example, a music file player, an e-Book reader, an electronic dictionary, and a mobile phone, are being replaced by smart devices that actually perform PC functions. Therefore, a variety of services based on mobile applications, for example, universal device synchronization and file sharing, are becoming commercialized and common. Terminals having sophisticated functions with a variety of sizes and specifications have been released.
However, despite the popularity of such smart devices, development of terminal management technology has not significantly progressed. In particular, a terminal fault needs to be automatically managed in real time. However a variety of software fault problems can occur in a terminal device, and it is difficult for a personal user to analyze the terminal fault and to address associated problems directly.
Meanwhile, as the smart device is recognized as an important network element, remote terminal management technology has become a big issue for smart device manufacturers as well as application service providers for smart devices. However, operators have a big burden of costs in terms of capital expenditures (CAPEX) and operational expenditures (OPEX) with a conventional passive type of terminal management. Accordingly, it is urgent to provide an automated terminal fault management framework for terminal-based service markets.
Meanwhile, in order to overcome limitations on passive analysis methods that depend on a service operator for determining abnormalities of the terminal, a method in which static rules or policies were defined and faults were accordingly detected and analyzed based on If/Else statements has been mainly applied conventionally. However, such conventional methods have a problem in that the number of rules becomes massive when a size of networks configured with terminals increases.
As an alternative method, a method in which a separate threshold is set to an individual performance indicator and the fault is determined by merely observing breach of the threshold has been proposed. However, in reality, it is difficult to set appropriate thresholds, and it has a disadvantage in that the threshold value needs to be continuously recalibrated according to states of the terminal and the network even when an initial threshold was accurate.
As an improved method, a method based on pattern matching is being studied but has a problem in that it is difficult to apply determination formulas and it needs a large amount of calculation to determine the fault.
Moreover, the above-described three methods have a disadvantage in that they include many errors in detection and analysis since they are based on binary decision to determine whether there is a fault. That is, since those detection techniques based on simplified information have structural vulnerability causing information loss, they have low effectiveness when applied to actual systems.